---
license: other
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- EllieS/Temp-L2-DPO
model-index:
- name: llama3-L1-SFT-L2-KTO
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# llama3-L1-SFT-L2-KTO

This model is a fine-tuned version of [EllieS/TempReason-L1-llama3](https://huggingface.co/EllieS/TempReason-L1-llama3) on the EllieS/Temp-L2-DPO dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2122
- Rewards/chosen: 0.3257
- Rewards/rejected: -9.5548
- Rewards/accuracies: 1.0
- Rewards/margins: 9.8805
- Logps/rejected: -1018.5145
- Logps/chosen: -12.0858
- Logits/rejected: 1.0988
- Logits/chosen: 0.1932

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.2129        | 0.4994 | 1000 | 0.2124          | 0.3252         | -9.3514          | 1.0                | 9.6766          | -998.1762      | -12.1315     | 1.1081          | 0.2036        |
| 0.2118        | 0.9989 | 2000 | 0.2122          | 0.3257         | -9.5548          | 1.0                | 9.8805          | -1018.5145     | -12.0858     | 1.0988          | 0.1932        |


### Framework versions

- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1